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Andrew MacLean

Key AI Takeaways From AHRA 2024

Adoption, Turnaround Time, Workflow
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The AHRA 2024 annual meeting offered a comprehensive exploration of the current landscape in medical imaging management. Yet it was surprising to find that out of 60+ sessions, only two directly addressed AI. Despite this, these sessions provided valuable insights into the evolving role of AI in medical imaging, emphasizing the need for industry leaders to stay ahead of the curve.

A Missed Opportunity?

Given the rapid advancements of AI, it was notable that there were no sessions specifically discussing the value of AI applied to imaging itself. The absence of such discussions may suggest a gap in the industry’s broader understanding of AI’s potential to impact clinical workflows and outcomes. However, the two sessions that did focus on AI were instrumental in highlighting its current and future applications, even in non-clinical settings.

AI’s Role in Imaging Operations

Les Jesbon, MHA, MBA, FACMPE, FACHE, LHRM, Regional Administrator at Prisma Health, provided a crucial perspective during his session titled “Artificial Intelligence – Non-Clinical Applications in Imaging Operations.” Jesbon made an important point – one echoed by other industry experts –  that while AI is not poised to replace jobs, those who ignore its potential do so at their own peril. This sentiment echoes a broader industry consensus that AI will play a pivotal role in shaping the future of imaging operations.

That aside, the session did shed light on several key themes:

  1. AI’s Focus on Clinical Throughput: Current AI in medical imaging primarily targets improving clinical throughput. These applications, cited by Jesbon, include diagnostic functions such as detecting pneumonia on chest radiographs or grading liver tumors, as well as repetitive tasks like breast or lung nodule detection. This emphasis on throughput highlights the potential for AI to alleviate workload pressures on radiologists and technologists, addressing the endemic workforce shortage in the field.
  2. Quantitative and Repetitive AI Applications: AI’s ability to handle high-volume, repetitive tasks and provide quantitative results – such as lung volume measurements on chest CTs or bone density assessments – demonstrates its growing importance in streamlining operations. As AI continues to evolve, its capacity to manage and interpret operational data will likely expand, offering further efficiencies in imaging departments.

Looking ahead, the future of AI in medical imaging is set to be transformative. The market for AI in imaging is projected to soar, reaching 14.2 billion by 2032. This growth will be driven by advancements in machine learning in healthcare, natural language processing and augmented intelligence, despite ongoing challenges related to data security and transparency.

Operational and Market Implications

The conference also touched on broader operational and market trends influenced by AI:

  • Shifts in Imaging Study Types: The proportion of CT scans as a percentage of total imaging studies may plateau or even decline in some markets, influenced by changes in technology, fees and reimbursement models. This trend verifies the importance of AI in optimizing imaging operations amidst rapidly evolving market conditions.
  • Regulatory and Market Dynamics: The elimination of market non-competes and Certificate of Need (CON) laws in certain states could lead to increased competition and further downward pricing pressures on hospital-based imaging departments. AI, with its ability to enhance efficiency and reduce costs, will be critical in helping these departments navigate these challenges.

AI’s Role in Shaping the Future of Radiology

A recent survey of thoracic radiologists revealed that over 60% expect AI to radically change their practice within the next decade. Furthermore, more than 80% anticipate that job satisfaction will improve or remain the same, suggesting that AI could enhance, rather than detract from, the radiology profession.

As the AHRA 2024 meeting demonstrated, while AI’s potential in medical imaging is immense, there remains a need for more focused discussions on its clinical applications. The industry must continue to explore and embrace AI’s capabilities to ensure that healthcare providers are not left behind in this constantly expanding frontier of medical imaging. 

AI is not just a tool for the future – it’s a critical component of the present, and its role in improving imaging operations and clinical outcomes can’t be overstated. As we move forward, it’s essential to continue engaging and exploring AI’s full potential in medical imaging, ensuring that its benefits are actualized across the entire spectrum of care.

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Andrew MacLean

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